Author Of 1 Presentation
P0559 - Cluster Analysis discriminates Multiple Sclerosis Patients based on Lesion Size and Myelin Content (ID 1884)
Abstract
Background
Clinical heterogeneity among patients with multiple sclerosis (MS) may be driven by genetic and environmental influences that lead to distinctive MRI features.
Objectives
Our objective was to utilize a cluster analysis to determine the variability of quantitative MRI features among a cohort of MS patients and examine the ability of these imaging features to discriminate patients by clinical disability.
Methods
Ninety-six relapsing remitting MS patients and 7 patients with progressive MS underwent Fast Acquisition with Spiral Trajectory and T2prep (FAST-T2) sequence, for myelin water fraction (MWF) analysis, and conventional MRI for measures of lesion volume, cortical thickness and thalamic volume. An agglomerative hierarchical clustering algorithm was implemented using lesion level MRI features selected from a Principal Component Analysis (PCA). The final clusters were selected by implementing a comprehensive validation method based on several unsupervised statistical learning techniques. Matched cluster groups with statistically significant clinical covariates (i.e. age and disease duration) were analyzed based on propensity scores.
Results
A total of 1691 chronic MS lesions were identified among the 103 MS patients. Mean patient age was 44.4 (+/- 11.9) years, disease duration was 10.5 (+/- 8.3) years, and expanded disability status scale (EDSS) was 2.2 (+/- 2.0). PCA demonstrated lesion MWF and volume distributions characterized by 25th, 50th and 75th percentiles account for 87% of the total variability. The hierarchical clustering confirmed two distinct patient clusters. The variables in order of importance were individual lesion median MWF, MWF 25th, MWF 75th, volume 75th percentiles, median individual lesion volume, and total lesion volume (all p-values < 0.000001). Cortical thickness and thalamic volume were significant but less important on cluster discrimination. The clustering MRI features discriminated patients based upon EDSS, p=0.0016 at the time of MRI and maintained EDSS difference at five years (n=72), p=0.0016.
Conclusions
The size and extent of demyelination among individual lesions discriminated MS patients into two MRI lesion-based clusters and was associated with clinical disability. These results suggest an inherent difference among patients with regard to lesion pathology and repair.